About the Role
Join a paid talent pool supporting projects in AI agents and reinforcement learning. You will help build practice environments and evaluate agent behavior, supporting the development of AI systems that interact with software and workflows.
What You'll Do
Build reinforcement learning environments in Python and Docker where agents can take actions and receive feedback.
Turn business workflows, such as ERP processes, CRM updates, and spreadsheet operations, into trainable scenarios.
Write tasks, connect tools and REST APIs, and create systems to verify agent actions.
Create and grade agent demonstrations, including screen recordings of task execution.
Collect execution traces, evaluate agent trajectories, and investigate failures.
What We're Looking For
Zero to five years of experience in software engineering, QA automation, machine learning or reinforcement learning engineering, operations analysis, or substantial use of business software.
Experience writing Python or building automations or reports in Excel, Salesforce, or an ERP system.
Experience testing, scripting, or automating multi-step software tasks, such as test cases, API calls, or UI steps.
Familiarity with Docker, REST APIs, or Gymnasium and OpenAI Gym-style environments is useful.
Experience with pytest, Playwright, or Selenium, or documenting business workflows and screen-based tasks, is useful.
Strong software fundamentals or hands-on knowledge of business workflows; prior AI data experience is not required.
Compensation & Benefits
Compensation is $35 to $70 per hour, depending on the project, field, and experience. Payment is based on hours worked.
Location
Remote. Projects typically last from one week to several months.